Unified Structural-Hydrodynamic Modeling of Underwater Underactuated Mechanisms and Soft Robots

2026-03-09

AI Summary

Modeling underactuated and soft-bodied underwater robots requires simultaneous identification of high-dimensional structural parameters and complex hydrodynamic coefficients—a highly challenging task. This work proposes a trajectory-driven global optimization framework that jointly estimates elastic, damping, and distributed hydrodynamic parameters by matching simulated and experimental trajectories. For the first time, this approach enables unified identification of both structural and fluid dynamic parameters without manual tuning. The method demonstrates strong cross-system transferability: when applied to an underactuated mechanism, it achieves end-effector position errors below 5%, and successfully transfers to an octopus-inspired soft arm, yielding a behaviorally realistic eight-armed swimming robot without additional calibration.

Technology Category

Intelligent Robots: State EstimationSearch and Optimization: Sampling/Simulation-based SearchHumans and AI: Human-Aware Planning and Behavior Prediction

Application Category

Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deploymentsGraph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphsUser Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

Underwater robots are widely deployed for ocean exploration and manipulation. Underactuated mechanisms are particularly advantageous in aquatic environments, as reducing actuator count lowers the risk of motor leakage while introducing inherent mechanical compliance. However, accurate modeling of underwater underactuated and soft robotic systems remains challenging because it requires identifying a high-dimensional set of internal structural and external hydrodynamic parameters. In this work, we propose a trajectory-driven global optimization framework for unified structural-hydrodynamic modeling of underwater multibody systems. Inspired by the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), the proposed approach simultaneously identifies coupled internal elastic, damping, and distributed hydrodynamic parameters through trajectory-level matching between simulation and experimental motion. This enables high-fidelity reproduction of both underactuated mechanisms and compliant soft robotic systems in underwater environments. We first validate the framework on a link-by-link underactuated multibody mechanism, demonstrating accurate identification of distributed hydrodynamic coefficients, with a normalized end effector position error below 5% across multiple trajectories, varying initial conditions, and both active-passive and fully passive configurations. The identified modeling strategy is then transferred to a single octopus-inspired soft arm, showing strong real-to-sim consistency without manual retuning. Finally, eight identified arms are assembled into a swimming octopus robot, where the unified parameter set enables realistic whole body behavior without additional parameter calibration. These results demonstrate the scalability and transferability of the proposed structural-hydrodynamic modeling framework across underwater underactuated and soft robotic systems.

Problem

• underwater robotics
• underactuated mechanisms
• soft robots
• structural-hydrodynamic modeling
• parameter identification

Innovation

• underactuated robotics
• soft robotics
• hydrodynamic modeling
• parameter identification
• trajectory-driven optimization